400 Caller's project doesn't match parent project - python-3.x

I have this block of code that basically translates text from one language to another using the cloud translate API. The problem is that this code always throws the error: "Caller's project doesn't match parent project". What could be the problem?
translation_separator = "translated_text: "
language_separator = "detected_language_code: "
translate_client = translate.TranslationServiceClient()
# parent = translate_client.location_path(
# self.translate_project_id, self.translate_location
# )
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = (
os.getcwd()
+ "/translator_credentials.json"
)
# Text can also be a sequence of strings, in which case this method
# will return a sequence of results for each text.
try:
result = str(
translate_client.translate_text(
request={
"contents": [text],
"target_language_code": self.target_language_code,
"parent": f'projects/{self.translate_project_id}/'
f'locations/{self.translate_location}',
"model": self.translate_model
}
)
)
print(result)
except Exception as e:
print("error here>>>>>", e)

Your issue seems to be related to the authentication method that you are using on your application, please follow the guide for authention methods with the translate API. If you are trying to pass the credentials using code, you can explicitly point to your service account file in code with:
def explicit():
from google.cloud import storage
# Explicitly use service account credentials by specifying the private key
# file.
storage_client = storage.Client.from_service_account_json(
'service_account.json')
Also, there is a codelab for getting started with the translation API with Python, this is a great step by step getting started guide for running the translate API with Python.
If the issue persists, you can try creating a Public Issue Tracker for Google Support

Related

ML Studio language studio failing to detect the source language

I am running a program in python to detect a language and translate that to English using azure machine learning studio. The code block mentioned below throwing error when trying to detect the language.
Error 0002: Failed to parse parameter.
def sample_detect_language():
print(
"This sample statement will be translated to english from any other foreign language"
)
from azure.core.credentials import AzureKeyCredential
from azure.ai.textanalytics import TextAnalyticsClient
endpoint = os.environ["AZURE_LANGUAGE_ENDPOINT"]
key = os.environ["AZURE_LANGUAGE_KEY"]
text_analytics_client = TextAnalyticsClient(endpoint=endpoint)
documents = [
"""
The feedback was awesome
""",
"""
la recensione รจ stata fantastica
"""
]
result = text_analytics_client.detect_language(documents)
reviewed_docs = [doc for doc in result if not doc.is_error]
print("Check the languages we got review")
for idx, doc in enumerate(reviewed_docs):
print("Number#{} is in '{}', which has ISO639-1 name '{}'\n".format(
idx, doc.primary_language.name, doc.primary_language.iso6391_name
))
if doc.is_error:
print(doc.id, doc.error)
print(
"Storing reviews and mapping to their respective ISO639-1 name "
)
review_to_language = {}
for idx, doc in enumerate(reviewed_docs):
review_to_language[documents[idx]] = doc.primary_language.iso6391_name
if __name__ == '__main__':
sample_detect_language()
Any help to solve the issue is appreciated.
The issue was raised because of missing the called parameters in the function. While doing language detection in machine learning studio, we need to assign end point and key credentials. In the code mentioned above, endpoint details were mentioned, but missed AzureKeyCredential.
endpoint = os.environ["AZURE_LANGUAGE_ENDPOINT"]
key = os.environ["AZURE_LANGUAGE_KEY"]
text_analytics_client = TextAnalyticsClient(endpoint=endpoint)
replace the above line with the code block mentioned below
text_analytics_client = TextAnalyticsClient(endpoint=endpoint, credential= AzureKeyCredential(key))

Google cloud function (python) does not deploy - Function failed on loading user code

I'm calling a simple python function in google cloud but cannot get it to save. It shows this error:
"Function failed on loading user code. This is likely due to a bug in the user code. Error message: Error: please examine your function logs to see the error cause: https://cloud.google.com/functions/docs/monitoring/logging#viewing_logs. Additional troubleshooting documentation can be found at https://cloud.google.com/functions/docs/troubleshooting#logging. Please visit https://cloud.google.com/functions/docs/troubleshooting for in-depth troubleshooting documentation."
Logs don't seem to show much that would indicate error in the code. I followed this guide: https://blog.thereportapi.com/automate-a-daily-etl-of-currency-rates-into-bigquery/
With the only difference environment variables and the endpoint I'm using.
Code is below, which is just a get request followed by a push of data into a table.
import requests
import json
import time;
import os;
from google.cloud import bigquery
# Set any default values for these variables if they are not found from Environment variables
PROJECT_ID = os.environ.get("PROJECT_ID", "xxxxxxxxxxxxxx")
EXCHANGERATESAPI_KEY = os.environ.get("EXCHANGERATESAPI_KEY", "xxxxxxxxxxxxxxx")
REGIONAL_ENDPOINT = os.environ.get("REGIONAL_ENDPOINT", "europe-west1")
DATASET_ID = os.environ.get("DATASET_ID", "currency_rates")
TABLE_NAME = os.environ.get("TABLE_NAME", "currency_rates")
BASE_CURRENCY = os.environ.get("BASE_CURRENCY", "SEK")
SYMBOLS = os.environ.get("SYMBOLS", "NOK,EUR,USD,GBP")
def hello_world(request):
latest_response = get_latest_currency_rates();
write_to_bq(latest_response)
return "Success"
def get_latest_currency_rates():
PARAMS={'access_key': EXCHANGERATESAPI_KEY , 'symbols': SYMBOLS, 'base': BASE_CURRENCY}
response = requests.get("https://api.exchangeratesapi.io/v1/latest", params=PARAMS)
print(response.json())
return response.json()
def write_to_bq(response):
# Instantiates a client
bigquery_client = bigquery.Client(project=PROJECT_ID)
# Prepares a reference to the dataset
dataset_ref = bigquery_client.dataset(DATASET_ID)
table_ref = dataset_ref.table(TABLE_NAME)
table = bigquery_client.get_table(table_ref)
# get the current timestamp so we know how fresh the data is
timestamp = time.time()
jsondump = json.dumps(response) #Returns a string
# Ensure the Response is a String not JSON
rows_to_insert = [{"timestamp":timestamp,"data":jsondump}]
errors = bigquery_client.insert_rows(table, rows_to_insert) # API request
print(errors)
assert errors == []
I tried just the part that does the get request with an offline editor and I can confirm a response works fine. I suspect it might have to do something with permissions or the way the script tries to access the database.

Algolia search python client to upload indexes behind a firewall

Building a search with Algolia search product for our Moodle site.
To update the index at Algolia site we want to use some automated process (upload the index data).
I decided to start with the Python client (Python v 3.9.x). Since we are working inside a corporate network we are behind the firewalls and there is a problem accessing algolia's servers.
I'm testing with two methods:
Search within already existing indices: index.search
update all indexes: index.replace_all_objects
Error message: 'Unreachable hosts'
Here is my code snippets:
# Search:
searchAppID = constants.ALGOLIA_APP_ID
searchKeyHash = constants.ALGOLIA_SEARCH_KEY
config = SearchConfig(searchAppID, searchKeyHash)
config.connect_timeout = 2
config.read_timeout = 5
config.write_timeout = 30
client = SearchClient.create_with_config(config)
index = client.init_index('myIndex')
result = index.search('SearchString')
# function to update index using json file:
def replace_IdxObj(client,index,fileName):
try:
if (index.exists()):
with open(fileName, encoding="utf8") as f:
data = json.load(f)
result = index.replace_all_objects(data, { 'autoGenerateObjectIDIfNotExist' : True })
return result
else:
print('No Index found! Cancel operation... \n')
return None
except Exception as err:
print ("Error: " + str(err))
When I test my code outside of the company's network - it's all ok!
Also I have a SSL certificate that could be used to work with external resources, so I used it in the following test (running from company's network behind the firewall):
response = requests.get('https://google.com/', verify=("C:\\Program Files\\Common Files\\SSL\\certs\\cert.cer"))
print(response)
This test works just fine (I'm getting 200 response)!
Please advise are there any ways to make Python process (which is used by algolia's python client) to use the certificate that I have ??? Any alternatives?
Many thanks!

How to do transactions using on google cloud datastore using google-cloud-ndb library in python3

Hi I am developing an application in python3 using the flask frame work that is going to run on appengine standard that uses cloud datastore for persistence
I want to perform transactions
so I tried the following i
#ndb.transactional()
def update_user(req_data):
print("running for req")
print(req_data)
query = TestUser.query(ndb.AND(TestUser.age=="1"))
with client.context():
result = query.get()
if result.name == "the one":
print("not writing")
return
else:
print(result.name+ " is not equal to 'the one'")
print(result.name)
result.name = req_data["name"]
result.put()
print("transaction ended")
#app.route('/test_req',methods=['POST'])
def test_req_handler():
req_data = request.get_json()
update_user(req_data)
print(req_data)
return "ok"
In the local development environment when I hit the handler /test_req I am getting the following error
\lib\site-packages\google\cloud\ndb\context.py", line 72, in get_context
raise exceptions.ContextError()
google.cloud.ndb.exceptions.ContextError: No current context. NDB calls must be made in context established by google.cloud.ndb.Client.context.
when I remove the #ndb.transactional() decorator entities gets updated and there is no error
In the original Cloud Datastore the only queries allowed in transactions are ancestor queries. The emulator is still enforcing this restriction. This change is noted in https://cloud.google.com/datastore/docs/upgrade-to-firestore .

i want to list all Resource in organisations using python function in google cloud

I went through the official docs of google cloud but I don't have an idea how to use these to list resources of specific organization by providing the organization id
organizations = CloudResourceManager.Organizations.Search()
projects = emptyList()
parentsToList = queueOf(organizations)
while (parent = parentsToList.pop()) {
// NOTE: Don't forget to iterate over paginated results.
// TODO: handle PERMISSION_DENIED appropriately.
projects.addAll(CloudResourceManager.Projects.List(
"parent.type:" + parent.type + " parent.id:" + parent.id))
parentsToList.addAll(CloudResourceManager.Folders.List(parent))
}
organizations = CloudResourceManager.Organizations.Search()
projects = emptyList()
parentsToList = queueOf(organizations)
while (parent = parentsToList.pop()) {
// NOTE: Don't forget to iterate over paginated results.
// TODO: handle PERMISSION_DENIED appropriately.
projects.addAll(CloudResourceManager.Projects.List(
"parent.type:" + parent.type + " parent.id:" + parent.id))
parentsToList.addAll(CloudResourceManager.Folders.List(parent))
}
You can use Cloud Asset Inventory for this. I wrote this code for performing a sink in BigQuery.
import os
from google.cloud import asset_v1
from google.cloud.asset_v1.proto import asset_service_pb2
def asset_to_bq(request):
client = asset_v1.AssetServiceClient()
parent = 'organizations/{}'.format(os.getEnv('ORGANIZATION_ID'))
output_config = asset_service_pb2.OutputConfig()
output_config.bigquery_destination.dataset = 'projects/{}}/datasets/{}'.format(os.getEnv('PROJECT_ID'),
os.getEnv('DATASET'))
output_config.bigquery_destination.table = 'asset_export'
output_config.bigquery_destination.force = True
response = client.export_assets(parent, output_config)
# For waiting the finish
# response.result()
# Do stuff after export
return "done", 200
if __name__ == "__main__":
asset_to_bq('')
Be careful is you use it, the sink must be done in an empty/not existing table or set the force to true.
In my case, some minutes after the Cloud Scheduler that trigger my function and extract the data to BigQuery, I have a Scheduled Query into BigQuery that copy the data to another table, for keeping the history.
Note: It's also possible to configure an extract in Cloud Storage if you prefer.
I hope that is a starting point for you and for achieving what do you want to do.
I am able to list the project but I also want to list the folder and resources under folder and folder.name and tags and i also want to specify the organization id to resources information from a specific organization
import os
from google.cloud import resource_manager
def export_resource (organizations):
client = resource_manager.Client()
for project in client.list_projects():
print("%s, %s" % (project.project_id, project.status))

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